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时间变系数自回归条件异方差模型 (TVP-ARCH)×EGARCH model×
领域计量经济学计量经济学
方法族Regression modelRegression model
起源年份1980s–1990s1991
提出者Extension of Engle (1982) ARCH; TVP-ARCH formalization credited to Nicholls & Quinn and subsequent state-space literatureDaniel B. Nelson
类型Conditional heteroscedasticity model with time-varying coefficientsVolatility / conditional variance model
开创性文献Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗
别名TVP-ARCH, time-varying ARCH, adaptive ARCH, state-space ARCHExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
相关56
摘要The Time-Varying Parameter ARCH (TVP-ARCH) model extends the classic ARCH framework by allowing both the conditional mean coefficients and the ARCH variance parameters to drift over time according to a random-walk or state-space process. This makes it possible to capture structural shifts in volatility dynamics without imposing a fixed parameter regime.The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.
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  1. v1
  2. 2 来源
  3. PUBLISHED

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ScholarGate方法对比: Time-varying parameter ARCH model · EGARCH model. 于 2026-06-17 检索自 https://scholargate.app/zh/compare